Tumors and lesions are types of pathological anatomies characterized by abnormal growth of tissue resulting from the uncontrolled, progressive multiplication of cells, while serving no physiological function.
Pathological anatomies can be treated with an invasive procedure, such as surgery, but can be harmful and full of risks for the patient. A non-invasive method to treat a pathological anatomy (e.g., tumor, legion, vascular malformation, nerve disorder, etc.) is external beam radiation therapy. In one type of external beam radiation therapy, an external radiation source is used to direct a sequence of x-ray beams at a tumor site from multiple angles, with the patient positioned so the tumor is at the center of rotation (isocenter) of the beam. As the angle of the radiation source changes, every beam passes through the tumor site, but passes through a different area of healthy tissue on its way to the tumor. As a result, the cumulative radiation dose at the tumor is high and the average radiation dose to healthy tissue is low.
The term “radiotherapy” refers to a procedure in which radiation is applied to a target region for therapeutic, rather than necrotic, purposes. The amount of radiation utilized in radiotherapy treatment sessions is typically about an order of magnitude smaller, as compared to the amount used in a radiosurgery session. Radiotherapy is typically characterized by a low dose per treatment (e.g., 100-200 centiGray (cGy)), short treatment times (e.g., 10 to 30 minutes per treatment) and hyperfractionation (e.g., 30 to 45 days of treatment). For convenience, the term “radiation treatment” is used herein to mean radiosurgery and/or radiotherapy unless otherwise noted by the magnitude of the radiation.
Conventional isocentric radiosurgery systems (e.g., the Gamma Knife) use forward treatment planning. In forward treatment planning, a medical physicist determines the radiation dose to be applied to a tumor and then calculates how much radiation will be absorbed by critical structures (i.e., vital organs) and other healthy tissue. There is no independent control of the two dose levels for a given number of beams, because the volumetric energy density at any given distance from the isocenter is a constant, no matter where the isocenter is located.
In inverse planning, in contrast to forward planning, the medical physicist specifies the minimum dose to the tumor and the maximum dose to other healthy tissues independently, and the treatment planning software then selects the direction, distance, and total number and energy of the beams in order to achieve the specified dose conditions. Conventional treatment planning software packages are designed to import 3-D images from a diagnostic imaging source, for example, computerized x-ray tomography (CT) scans. CT is able to provide an accurate three-dimensional model of a volume of interest (e.g., skull or other tumor bearing portion of the body) generated from a collection of CT slices and, thereby, the volume requiring treatment can be visualized in three dimensions.
During inverse planning, a volume of interest (VOI) is used to delineate structures to be targeted or avoided with respect to the administered radiation dose. That is, the radiation source is positioned in a sequence calculated to localize the radiation dose into a VOI that as closely as possible conforms to the tumor requiring treatment, while avoiding exposure of nearby healthy tissue. Once the target (e.g., tumor) VOI has been defined, and the critical and soft tissue volumes have been specified, the responsible radiation oncologist or medical physicist specifies the minimum radiation dose to the target VOI and the maximum dose to normal and critical healthy tissue. The software then produces the inverse treatment plan, relying on the positional capabilities of the radiation treatment system, to meet the min/max dose constraints of the treatment plan.
FIG. 1 is a conceptual illustration of a graphical output of a treatment planning software displaying a slice of a CT image. The illustration of the CT image includes a pathological anatomy that is targeted for treatment, and well as a critical region that is positioned near the pathological anatomy. The treatment planning software enables the generation of a critical region contour around the critical region and a target region contour around the pathological anatomy. Conventionally, a user manually delineates points (e.g., some of the dots on the contour lines of FIG. 1) on the display that is used by the treatment planning software to generate the corresponding contours. While this may seem an easy task, such matching is difficult due to the three-dimensional nature and irregularities of the pathological and normal anatomies, and the limited number of beam positions available from the radiation beam source. Based on specified minimum dose to the target region and the maximum dose to the critical region, the treatment planning software generates a dose isocontour for the target region. The dose isocontour represents a given dose percentage (e.g., 60%, 70%, 80%, etc.) of a specified prescription dose for the target region. Ideally, the dose isocontour should perfectly match the contour of the target region. In some cases, the dose isocontour generated by the treatment planning software is not optimal, and can include portions of the critical region, as illustrated in FIG. 1.
The two principal requirements for an effective radiation treatment system are homogeneity and conformality. Homogeneity is the uniformity of the radiation dose over the volume of the target (e.g., pathological anatomy such as a tumor, lesion, vascular malformation, etc.) characterized by a dose volume histogram (DVH). An ideal DVH for the pathological anatomy would be a rectangular function as illustrated in FIG. 2, where the dose is 100 percent of the prescribed dose over the volume of the pathological anatomy and zero elsewhere. A desirable DVH for a critical region would have the profile illustrated in FIG. 3, where the volume of the critical anatomical structures receives as little of the prescribed dose as possible.
Conformality is the degree to which the radiation dose matches (conforms) to the shape and extent of the target (e.g., tumor) in order to avoid damage to critical adjacent structures. More specifically, conformality is a measure of the amount of prescription (Rx) dose (amount of dose applied) within a target VOI. Conformality may be measured using a conformality index (CI)=total volume at>=Rx dose/target volume at>=Rx dose. Perfect conformality results in a CI=1. With conventional radiotherapy treatment, using treatment planning software, a clinician identifies a dose isocontour for a corresponding VOI for application of a treatment dose (e.g., 3000 cGy).
The treatment planning process typically requires a user to employ a treatment planning software program to complete several planning functions. The user interface of the treatment planning software guides the user to complete the treatment plan. For example, the first step in treatment planning may be selecting and loading patient data into the treatment planning software program. This function allows the user to load previously saved plans, start a new plan by loading DICOM formatted patient data, including volumes of interest pushed as DICOM RT structure sets, recover the last plan worked on, or delete a previously saved plan. For example, the load function may involve three tasks that are performed within a single user-interface window, as shown in FIG. 4. The first task may be to select a fixed image (e.g., CT image) for the patient by selecting the patient, study, and series. A similar process may be performed for selecting a moving image (e.g., MR, PET). One problem associated with the load function is that because multiple tasks are performed within a single user-interface window, the load function may be confusing or overly complicated for some users, particularly users that are new to the treatment planning software program.
The treatment planning software typically allows the user to set display preferences and defaults for such settings as Isocurve parameters, VOI Set parameters, and density model for dose calculations. Because treatment plans differ from patient to patient, as well as from treatment region to treatment region (e.g., cranial versus lung), the treatment planning software requires the user to input parameters throughout the treatment planning process. One problem with such a process is that the chances of user based errors are increased because of the number of manual inputs. Moreover, such manual tasks are time consuming and may unnecessarily increase the overall time spent on treatment planning.
The treatment planning software may also provide the option to set preferences through a preference screen, for example, as shown in FIG. 5. One problem with such preference screens is that they may be limited to basic settings and do not allow the user to set parameters related to a treatment plan. For example, the preference screen may be limited to colors for isocurve lines and colors for various VOI names.